The NIH’s Researching COVID to Enhance Recovery (RECOVER) Initiative used a cohort study of more than 10,000 individuals with and without previous COVID-19 diagnoses and compared samples using 25 common laboratory tests in hopes a useful biomarker could be identified. They were unsuccessful.
Long COVID—or PASC—is an umbrella term for those with persistent post-COVID infection symptoms that negatively impact quality of life. Though it affects millions worldwide and has been called a major public health burden, the NIH/Langone study scientists noted one glaring problem: PASC is defined differently in the major tests they studied. This makes consistent diagnoses difficult.
The study brought to light possible roadblocks that prevented biomarker identification.
“This study is an important step toward defining long COVID beyond any one individual symptom,” said study author Leora Horwitz, MD (above), director of the Center for Healthcare Innovation and Delivery Science and co-principal investigator for the RECOVER CSC at NYU Langone, in a Langone Health news release. “This definition—which may evolve over time—will serve as a critical foundation for scientific discovery and treatment design.” In the future, clinical laboratories may be tasked with finding combinations of routine and reference tests that, together, enable a more precise and earlier diagnosis of long COVID. (Photo copyright: Yale School of Medicine.)
NIH/Langone Study Details
“The study … examined 25 routinely used and standardized laboratory tests chosen based on availability across institutions, prior literature, and clinical experience. These tests were conducted prospectively in laboratories that are certified by the Clinical Laboratory Improvement Amendments (CLIA). The samples were collected from 10,094 RECOVER-Adult participants, representing a diverse cohort from all over the US,” Inside Precision Medicine reported.
However, the scientists found no clinical laboratory “value” among the 25 tests examined that “reliably indicate previous infection, PASC, or the particular cluster type of PASC,” Inside Precision Medicine noted, adding that “Although some minor differences in the results of specific laboratory tests attempted to differentiate between individuals with and without a history of infection, these findings were generally clinically meaningless.”
“In a cohort study of more than 10,000 participants with and without prior SARS-CoV-2 infection, we found no evidence that any of 25 routine clinical laboratory values provide a reliable biomarker of prior infection, PASC, or the specific type of PASC cluster. … Overall, no evidence was found that any of the 25 routine clinical laboratory values assessed in this study could serve as a clinically useful biomarker of PASC,” the study authors wrote in Annals of Internal Medicine.
In addition to a vague definition of PASC, the NIH/Langone researchers noted a few other potential problems identifying a biomarker from the research.
“Use of only selected biomarkers, choice of comparison groups, if any (people who have recovered from PASC or healthy control participants); duration of symptoms; types of symptoms or phenotypes; and patient population features, such as sex, age, race, vaccination status, comorbidities, and severity of initial infection,” could be a cause for ambiguous results, the scientists wrote.
Future Research
“Understanding the basic biological underpinnings of persistent symptoms after SARS-CoV-2 infection will likely require a rigorous focus on investigations beyond routine clinical laboratory studies (for example, transcriptomics, proteomics, metabolomics) to identify novel biomarkers,” the study authors wrote in Annals of Internal Medicine.
“Our challenge is to discover biomarkers that can help us quickly and accurately diagnose long COVID to ensure people struggling with this disease receive the most appropriate care as soon as possible,” said David Goff, MD, PhD, director of the division of cardiovascular sciences at the NIH’s National Heart, Lung, and Blood Institute, in an NHLBI news release. “Long COVID symptoms can prevent someone from returning to work or school, and may even make everyday tasks a burden, so the ability for rapid diagnosis is key.”
“Approximately one in 20 US adults reported persisting symptoms after COVID-19 in June 2024, with 1.4% reporting significant limitations,” the NIH/Langone scientists wrote in their published study.
Astute clinical laboratory scientists will recognize this as possible future diagnostic testing. There is no shortage of need.
Scientists turned to metabolomics to find cause of biological aging and release index of 25 metabolites that predict healthy and rapid agers
Researchers at the University of Pittsburg Medical Center and the University of Pittsburgh School of Medicine have identified biomarkers in human blood which appear to affect biological aging (aka, senescence). Since biological aging is connected to a person’s overall condition, further research and studies confirming UPMC’s findings will likely lead to a new panel of tests clinical laboratories can run to support physicians’ assessment of their patients’ health.
UPMC’s research “points to pathways and compounds that may underlie biological age, shedding light on why people age differently and suggesting novel targets for interventions that could slow aging and promote health span, the length of time a person is healthy,” according to a UPMC news release.
“We decided to look at metabolites because they’re very dynamic,” Aditi Gurkar, PhD, the study’s senior author, told the Pittsburgh Post-Gazette. Gurkar is Assistant Professor of Medicine, Division of Geriatric Medicine, Aging Institute at the University of Pittsburg. “They can change because of the diet, they can change because of exercise, they can change because of lifestyle changes like smoking,” she added.
The scientists identified 25 metabolites that “showed clear differences” in the metabolomes of both healthy and rapid agers. Based on those findings, the researchers developed the Healthy Aging Metabolic (HAM) Index, a panel of metabolites that predicted healthy agers regardless of gender or race.
“Age is more than just a number,” said Aditi Gurkar, PhD (above), Assistant Professor of Geriatric Medicine at University of Pittsburg School of Medicine and the study’s senior author in a news release. “Imagine two people aged 65: One rides a bike to work and goes skiing on the weekends and the other can’t climb a flight of stairs. They have the same chronological age, but very different biological ages. Why do these two people age differently? This question drives my research.” Gurkar’s research may one day lead to new clinical laboratory tests physicians will order when evaluating their patients’ health. (Photo copyright: University of Pittsburg.)
Clear Differences in Metabolites
According to the National Cancer Institute, a metabolite is a “substance made or used when the body breaks down food, drugs, or chemicals, or its own tissue (for example, fat or muscle tissue). This process, called metabolism, makes energy and the materials needed for growth, reproduction, and maintaining health. It also helps get rid of toxic substances.”
The UPMC researchers used metabolomics—the study of chemical process in the body that involves metabolites, other processes, and biproducts of cell metabolism—to create a “molecular fingerprint” of blood drawn from individuals in two separate study groups.
They included:
People over age 75 able to walk a flight of stairs or walk for 15 minutes without a break, and
People, age 65 to 75, who needed to rest during stair climbing and walk challenges.
The researchers found “clear differences” in the metabolomes of healthy agers as compared to rapid agers, suggesting that “metabolites in the blood could reflect biological age,” according to the UPMC news release.
“Other studies have looked at genetics to measure biological aging, but genes are very static. The genes you’re born with are the genes you die with,” said Gurkar in the news release.
Past studies on aging have explored other markers of biological age such as low grade-inflammation, muscle mass, and physical strength. But those markers fell short in “representing complexity of biological aging,” the UPMC study authors wrote in Aging Cell.
“One potential advantage of metabolomics over other ‘omic’ approaches is that metabolites are the final downstream products, and changes are closely related to the immediate (path) physiologic state of an individual,” they added.
The researchers used an artificial intelligence (AI) model that could identify “potential drivers of biological traits” and found three metabolites “that were most likely to promote healthy aging or drive rapid aging. In future research, they plan to delve into how these metabolites, and the molecular pathways that produce them, contribute to biological aging and explore interventions that could slow this process,” the new release noted.
“While it’s great that we can predict biological aging in older adults, what would be even more exciting is a blood test that, for example, can tell someone who’s 35 that they have a biological age more like a 45-year-old,” Gurkar said. “That person could then think about changing aspects of their lifestyle early—whether that’s improving their sleep, diet or exercise regime—to hopefully reverse their biological age.”
Looking Ahead
The UPMC scientists plan more studies to explore metabolites that promote healthy aging and rapid aging, and interventions to slow disease progression.
It’s possible that the blood-based HAM Index may one day become a diagnostic tool physicians and clinical laboratories use to aid monitoring of chronic diseases. As a commonly ordered blood test, it could help people find out biological age and make necessary lifestyle changes to improve their health and longevity.
With the incidence of chronic disease a major problem in the US and other developed countries, a useful diagnostic and monitoring tool like HAM could become a commonly ordered diagnostic procedure. In turn, that would allow clinical laboratories to track the same patient over many years, with the ability to use multi-year lab test data to flag patients whose biomarkers are changing in the wrong direction—thus enabling physicians to be proactive in treating their patients.
Findings could lead to deeper understanding of why we age, and to medical laboratory tests and treatments to slow or even reverse aging
Can humans control aging by keeping their genes long and balanced? Researchers at Northwestern University in Evanston, Illinois, believe it may be possible. They have unveiled a “previously unknown mechanism” behind aging that could lead to medical interventions to slow or even reverse aging, according to a Northwestern news release.
Should additional studies validate these early findings, this line of testing may become a new service clinical laboratories could offer to referring physicians and patients. It would expand the test menu with assays that deliver value in diagnosing the aging state of a patient, and which identify the parts of the transcriptome that are undergoing the most alterations that reduce lifespan.
It may also provide insights into how treatments and therapies could be implemented by physicians to address aging.
“I find it very elegant that a single, relatively concise principle seems to account for nearly all of the changes in activity of genes that happen in animals as they change,” Thomas Stoeger, PhD, postdoctoral scholar in the Amaral Lab who led the study, told GEN. Clinical laboratories involved in omics research may soon have new anti-aging diagnostic tests to perform. (Photo copyright: Amaral Lab.)
Possible ‘New Instrument’ for Biological Testing
Researchers found clues to aging in the length of genes. A gene transcript length reveals “molecular-level changes” during aging: longer genes relate to longer lifespans and shorter genes suggest shorter lives, GEN summarized.
The phenomenon the researchers uncovered—which they dubbed transcriptome imbalance—was “near universal” in the tissues they analyzed (blood, muscle, bone, and organs) from both humans and animals, Northwestern said.
According to the National Human Genome Research Institute fact sheet, a transcriptome is “a collection of all the gene readouts (aka, transcript) present in a cell” shedding light on gene activity or expression.
The Northwestern study suggests “systems-level” changes are responsible for aging—a different view than traditional biology’s approach to analyzing the effects of single genes.
“We have been primarily focusing on a small number of genes, thinking that a few genes would explain disease,” said Luis Amaral, PhD, Senior Author of the Study and Professor of Chemical and Biological Engineering at Northwestern, in the news release.
“So, maybe we were not focused on the right thing before. Now that we have this new understanding, it’s like having a new instrument. It’s like Galileo with a telescope, looking at space. Looking at gene activity through this new lens will enable us to see biological phenomena differently,” Amaral added.
In their Nature Aging paper, Amaral and his colleagues wrote, “We hypothesize that aging is associated with a phenomenon that affects the transcriptome in a subtle but global manner that goes unnoticed when focusing on the changes in expression of individual genes.
“We show that transcript length alone explains most transcriptional changes observed with aging in mice and humans,” they continued.
In tissues studied, older animals’ long transcripts were not as “abundant” as short transcripts, creating “imbalance.”
“Imbalance” likely prohibited the researchers’ discovery of a “specific set of genes” changing.
As animals aged, shorter genes “appeared to become more active” than longer genes.
In humans, the top 5% of genes with the shortest transcripts “included many linked to shorter life spans such as those involved in maintaining the length of telomeres.”
Conversely, the researchers’ review of the leading 5% of genes in humans with the longest transcripts found an association with long lives.
Antiaging drugs—rapamycin (aka, sirolimus) and resveratrol—were linked to an increase in long-gene transcripts.
“The changes in the activity of genes are very, very small, and these small changes involve thousands of genes. We found this change was consistent across different tissues and in different animals. We found it almost everywhere,” Thomas Stoeger, PhD, postdoctoral scholar in the Amaral Lab who led the study, told GEN.
In their paper, the Northwestern scientists noted implications for creation of healthcare interventions.
“We believe that understanding the direction of causality between other age-dependent cellular and transcriptomic changes and length-associated transcriptome imbalance could open novel research directions for antiaging interventions,” they wrote.
While more research is needed to validate its findings, the Northwestern study is compelling as it addresses a new area of transcriptome knowledge. This is another example of researchers cracking open human and animal genomes and gaining new insights into the processes supporting life.
For clinical laboratories and pathologists, diagnostic testing to reverse aging and guide the effectiveness of therapies may one day be possible—kind of like science’s take on the mythical Fountain of Youth.
The technology is similar to the concept of a liquid biopsy, which uses blood specimens to identify cancer by capturing tumor cells circulating in the blood.
According to the American Cancer Society, lung cancer is responsible for approximately 25% of cancer deaths in the US and is the leading cause of cancer deaths in both men and women. The ACS estimates there will be about 236,740 new cases of lung cancer diagnosed in the US this year, and about 130,180 deaths due to the disease.
Early-stage lung cancer is typically asymptomatic which leads to later stage diagnoses and lowers survival rates, largely due to a lack of early disease detection tools. The current method used to detect early lung cancer lesions is low-dose spiral CT imaging, which is costly and can be risky due to the radiation hazards of repeated screenings, the news release noted.
MGH’s newly developed diagnostic tool detects lung cancer from alterations in blood metabolites and may lead to clinical laboratory tests that could dramatically improve survival rates of the deadly disease, the MGH scientist noted in a news release.
“Our study demonstrates the potential for developing a sensitive screening tool for the early detection of lung cancer,” said Leo Cheng, PhD (above), in the news release. Cheng is Associate Professor of Radiology at Harvard Medical School and Associate Biophysicist in Radiology at Massachusetts General Hospital. “The predictive model we constructed can identify which people may be harboring lung cancer. Individuals with suspicious findings would then be referred for further evaluation by imaging tests, such as low-dose CT, for a definitive diagnosis,” he added. Oncologists may soon have a clinical laboratory test for screening patients with early-stage lung cancer. (Photo copyright: OCSMRM.)
Detecting Lung Cancer in Blood Metabolomic Profiles
The MGH scientists created their lung-cancer predictive model based on magnetic resonance spectroscopy which can detect the presence of lung cancer from alterations in blood metabolites.
The researchers screened tens of thousands of stored blood specimens and found 25 patients who had been diagnosed with non-small-cell lung carcinoma (NSCLC), and who had blood specimens collected both at the time of their diagnosis and at least six months prior to the diagnosis. They then matched these individuals with 25 healthy controls.
The scientists first trained their statistical model to recognize lung cancer by measuring metabolomic profiles in the blood samples obtained from the patients when they were first diagnosed with lung cancer. They then compared those samples to those of the healthy controls and validated their model by comparing the samples that had been obtained from the same patients prior to the lung cancer diagnosis.
The predictive model yielded values between the healthy controls and the patients at the time of their diagnoses.
“This was very encouraging, because screening for early disease should detect changes in blood metabolomic profiles that are intermediate between healthy and disease states,” Cheng noted.
The MGH scientists then tested their model with a different group of 54 patients who had been diagnosed with NSCLC using blood samples collected before their diagnosis. The second test confirmed the accuracy of their model.
Predicting Five-Year Survival Rates for Lung Cancer Patients
Values derived from the MGH predictive model measured from blood samples obtained prior to a lung cancer diagnosis also could enable oncologists to predict five-year survival rates for patients. This discovery could prove to be useful in determining clinical strategies and personalized treatment decisions.
The researchers plan to analyze the metabolomic profiles of the clinical characteristics of lung cancer to understand the entire metabolic spectrum of the disease. They hope to create similar models for other illnesses and have already created a model that can distinguish aggressive prostate cancer by measuring the metabolomics profiles of more than 400 patients with that disease.
In addition, they are working on a similar model to screen for Alzheimer’s disease using blood samples and cerebrospinal fluid.
More research and clinical studies are needed to validate the utilization of blood metabolomics models as early screening tools in clinical practice. However, this technology might provide pathologists and clinical laboratories with diagnostic tests for the screening of early-stage lung cancer that could save thousands of lives each year.
Genomic sequencing continues to benefit patients through precision medicine clinical laboratory treatments and pharmacogenomic therapies
EDITOR’S UPDATE—Jan. 26, 2022: Since publication of this news briefing, officials from Genomics England contacted us to explain the following:
The “five million genome sequences” was an aspirational goal mentioned by then Secretary of State for Health and Social Care Matt Hancock, MP, in an October 2, 2018, press release issued by Genomics England.
As of this date a spokesman for Genomics England confirmed to Dark Daily that, with the initial goal of 100,000 genomes now attained, the immediate goal is to sequence 500,000 genomes.
This goal was confirmed in a tweet posted by Chris Wigley, CEO at Genomics England.
In accordance with this updated input, we have revised the original headline and information in this news briefing that follows.
What better proof of progress in whole human genome screening than the announcement that the United Kingdom’s 100,000 Genome Project has not only achieved that milestone, but will now increase the goal to 500,000 whole human genomes? This should be welcome news to clinical laboratory managers, as it means their labs will be positioned as the first-line provider of genetic data in support of clinical care.
Many clinical pathologists here in the United States are aware of the 100,000 Genome Project, established by the National Health Service (NHS) in England (UK) in 2012. Genomics England’s new goal to sequence 500,000 whole human genomes is to pioneer a “lasting legacy for patients by introducing genomic sequencing into the wider healthcare system,” according to Technology Networks.
The importance of personalized medicine and of the power of precise, accurate diagnoses cannot be understated. This announcement by Genomics England will be of interest to diagnosticians worldwide, especially doctors who diagnose and treat patients with chronic and life-threatening diseases.
Building a Vast Genomics Infrastructure
Genetic sequencing launched the era of precision medicine in healthcare. Through genomics, drug therapies and personalized treatments were developed that improved outcomes for all patients, especially those suffering with cancer and other chronic diseases. And so far, the role of genomics in healthcare has only been expanding, as Dark Daily covered in numerous ebriefings.
Genomics England, which is wholly owned by the Department of Health and Social Care in the United Kingdom, was formed in 2012 with the goal of sequencing 100,000 whole genomes of patients enrolled in the UK National Health Service. That goal was met in 2018, and now the NHS aspires to sequence 500,000 genomes.
“The last 10 years have been really exciting, as we have seen genetic data transition from being something that is useful in a small number of contexts with highly targeted tests, towards being a central part of mainstream healthcare settings,” Richard Scott, MD, PhD (above), Chief Medical Officer at Genomics England told Technology Networks. Much of the progress has found its way into clinical laboratory testing and precision medicine diagnostics. (Photo copyright: Genomics England.)
Genomics England’s initial goals included:
To create an ethical program based on consent,
To set up a genomic medicine service within the NHS to benefit patients,
To make new discoveries and gain insights into the use of genomics, and
To begin the development of a UK genomics industry.
To gain the greatest benefit from whole genome sequencing (WGS), a substantial amount of data infrastructure must exist. “The amount of data generated by WGS is quite large and you really need a system that can process the data well to achieve that vision,” said Richard Scott, MD, PhD, Chief Medical Officer at Genomics England.
In early 2020, Weka, developer of the WekaFS, a fully parallel and distributed file system, announced that it would be working with Genomics England on managing the enormous amount of genomic data. When Genomics England reached 100,000 sequenced genomes, it had already gathered 21 petabytes of data. The organization expects to have 140 petabytes by 2023, notes a Weka case study.
Putting Genomics England’s WGS Project into Action
WGS has significantly impacted the diagnosis of rare diseases. For example, Genomics England has contributed to projects that look at tuberculosis genomes to understand why the disease is sometimes resistant to certain medications. Genomic sequencing also played an enormous role in fighting the COVID-19 pandemic.
Scott notes that COVID-19 provides an example of how sequencing can be used to deliver care. “We can see genomic influences on the risk of needing critical care in COVID-19 patients and in how their immune system is behaving. Looking at this data alongside other omics information, such as the expression of different protein levels, helps us to understand the disease process better,” he said.
What’s Next for Genomics Sequencing?
As the research continues and scientists begin to better understand the information revealed by sequencing, other areas of scientific study like proteomics and metabolomics are becoming more important.
“There is real potential for using multiple strands of data alongside each other, both for discovery—helping us to understand new things about diseases and how [they] affect the body—but also in terms of live healthcare,” Scott said.
Along with expanding the target of Genomics England to 500,000 genomes sequenced, the UK has published a National Genomic Strategy named Genome UK. This plan describes how the research into genomics will be used to benefit patients. “Our vision is to create the most advanced genomic healthcare ecosystem in the world, where government, the NHS, research and technology communities work together to embed the latest advances in patient care,” according to the Genome UK website.
Clinical laboratories professionals with an understanding of diagnostics will recognize WGS’ impact on the healthcare industry. By following genomic sequencing initiatives, such as those coming from Genomics England, pathologists can keep their labs ready to take advantage of new discoveries and insights that will improve outcomes for patients.
